U.S. patent number 11,449,700 [Application Number 17/077,658] was granted by the patent office on 2022-09-20 for enhanced matrix symbol error correction method.
This patent grant is currently assigned to HAND HELD PRODUCTS, INC.. The grantee listed for this patent is Hand Held Products, Inc.. Invention is credited to H. Sprague Ackley.
United States Patent |
11,449,700 |
Ackley |
September 20, 2022 |
Enhanced matrix symbol error correction method
Abstract
A system and method for error correction for machine-readable
symbols having data codewords, and having error correction (EC)
codewords derived from the data codewords and redundantly
indicating the location and data contents of the data codewords.
The symbols use Reed-Solomon (RS) error correction to retrieve
damaged codewords. RS error correction normally requires two EC
codewords to identify both the location and data contents of a data
codeword. The present system and method perform optical contrast
analysis on the codewords, identifying those codewords with the
lowest contrast levels. Codewords with the lowest contrast levels
are flagged as optically ambiguous, thereby marking, in the EC
equations, the locations of the codewords most like to be in error.
As a result, only a single EC codeword is required to retrieve the
data for a flagged data codeword.
Inventors: |
Ackley; H. Sprague (Seattle,
WA) |
Applicant: |
Name |
City |
State |
Country |
Type |
Hand Held Products, Inc. |
Charlotte |
NC |
US |
|
|
Assignee: |
HAND HELD PRODUCTS, INC.
(Charlotte, NC)
|
Family
ID: |
1000006573612 |
Appl.
No.: |
17/077,658 |
Filed: |
October 22, 2020 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20210073501 A1 |
Mar 11, 2021 |
|
Related U.S. Patent Documents
|
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
Issue Date |
|
|
16268721 |
Feb 6, 2019 |
10846498 |
|
|
|
15006561 |
Mar 19, 2019 |
10235547 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F
11/10 (20130101); G06K 7/1473 (20130101); G06K
7/14 (20130101); G06K 7/1417 (20130101) |
Current International
Class: |
G06K
7/14 (20060101); G06F 11/10 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
1402191 |
|
Mar 2003 |
|
CN |
|
103593695 |
|
Feb 2014 |
|
CN |
|
103903225 |
|
Jul 2014 |
|
CN |
|
104715221 |
|
Jun 2015 |
|
CN |
|
10-111904 |
|
Apr 1998 |
|
JP |
|
H10-171912 |
|
Jun 1998 |
|
JP |
|
2001-167222 |
|
Jun 2001 |
|
JP |
|
2013-148981 |
|
Aug 2013 |
|
JP |
|
10-2011-0002833 |
|
Jan 2011 |
|
KR |
|
2013/163789 |
|
Nov 2013 |
|
WO |
|
2013/173985 |
|
Nov 2013 |
|
WO |
|
2014/019130 |
|
Feb 2014 |
|
WO |
|
2014/110495 |
|
Jul 2014 |
|
WO |
|
Other References
CN Notice of Allowance dated Jan. 12, 2022 for CN Application No.
201710140373, 2 pages. cited by applicant .
English translation of CN Notice of Allowance dated Jan. 12, 2022
for CN Application No. 201710140373, 3 pages. cited by applicant
.
CN Office Action dated Aug. 4, 2021 for CN Application No.
201710140373, 6 pages. cited by applicant .
Decision to grant a European patent received for European
Application No. 17151685.9, dated Jul. 1, 2021, 2 pages. cited by
applicant .
English Translation of CN Office Action dated Aug. 4, 2021 for CN
Application No. 201710140373, 9 pages. cited by applicant .
English Translation of JP Decision to Grant dated Feb. 22, 2021 for
JP Application No. 2017007324, 2 pages. cited by applicant .
JP Decision to Grant dated Feb. 22, 2021 for JP Application No.
2017007324, 3 pages. cited by applicant .
Extended European search report and written opinion dated Nov. 22,
2021 for EP Application No. 21186794, 6 pages. cited by applicant
.
Advisory Action (PTOL-303) dated Feb. 21, 2018 for U.S. Appl. No.
15/006,561. cited by applicant .
Advisory Action (PTOL-303) dated Sep. 24, 2018 for U.S. Appl. No.
15/006,561. cited by applicant .
Annex to the communication dated Feb. 28, 2019 for EP Application
No. 17151685. cited by applicant .
Communication from the Examining Division dated Feb. 28, 2019 for
EP Application No. 17151685. cited by applicant .
English Translation of JP Office Action dated Nov. 17, 2020 for JP
Application No. 2017007324. cited by applicant .
English translation of JP Search report dated Nov. 11, 2020 for JP
Application No. 2017007324. cited by applicant .
European search opinion dated Jun. 16, 2017 for EP Application No.
17151685. cited by applicant .
European Search Report and Search Opinion Received for EP
Application No. 17151685.9, dated Jun. 16, 2017, 7 pages. cited by
applicant .
European search report dated Jun. 16, 2017 for EP Application No.
17151685. cited by applicant .
Examination Report in related European Application No. 17151685.9
dated Feb. 28, 2019, pp. 1-4. cited by applicant .
Extended Search Report in related European Application No.
17151685.9 dated Jun. 16, 2017, pp. 1-7. cited by applicant .
Final Rejection dated Dec. 4, 2017 for U.S. Appl. No. 15/006,561.
cited by applicant .
Final Rejection dated Jul. 11, 2018 for U.S. Appl. No. 15/006,561.
cited by applicant .
Furumoto, K., et al., Recognition Accuracy Improvement of QR Code
by Using GMD Decoding, IEICE Technical Report IT2014-27(Jul. 2014),
Jul. 10, 2014, vol. 114, No. 138, pp. 89-94, The Institute of
Electronics Information and Communication Engineers, Japan.
(Abstract Only). cited by applicant .
Hahn, H.I., et al., "Implementation of Algorithm to Decode
Two-Dimensional Barcode PDF-417", 6th International Conference on
Signal Processing, 2002, Conference Location: Beijing, China, Date
of Conference: Aug. 26-30, 2002, pp. 1791-1794. (Year:2002). cited
by applicant .
JP Office Action dated Nov. 17, 2020 for JP Application No.
2017007324. cited by applicant .
JP Search report dated Nov. 11, 2020 for JP Application No.
2017007324. cited by applicant .
Non-Final Rejection dated Apr. 9, 2020 for U.S. Appl. No.
16/268,721. cited by applicant .
Non-Final Rejection dated May 18, 2017 for U.S. Appl. No.
15/006,561. cited by applicant .
Notice of Allowance and Fees Due (PTOL-85) dated Jul. 23, 2020 for
U.S. Appl. No. 16/268,721. cited by applicant .
Notice of Allowance and Fees Due (PTOL-85) dated Nov. 1, 2018 for
U.S. Appl. No. 15/006,561. cited by applicant .
Office Action received for European Patent Application No.
17151685.9, dated Feb. 28, 2019, 4 pages. cited by applicant .
U.S. Appl. No. 13/367,978 for a Laser Scanning Module Employing an
Elastomeric U-Hinge Based Laser Scanning Assembly, filed Feb. 7,
2012 (Feng et al.), now abandoned. cited by applicant .
U.S. Appl. No. 14/277,337 for Multipurpose Optical Reader, filed
May 14, 2014 (Jovanovski et al.); 59 pages; now abandoned. cited by
applicant .
U.S. Appl. No. 14/283,282 for Terminal Having Illumination and
Focus Control filed May 21, 2014 (Liu et al.); 31 pages; now
abandoned. cited by applicant .
U.S. Appl. No. 14/446,391 for Multifunction Point of Sale Apparatus
With Optical Signature Capture filed Jul. 30, 2014 (Good et al.);
37 pages; now abandoned. cited by applicant .
U.S. Appl. No. 14/676,109 for Indicia Reader filed Apr. 1, 2015
(Huck); now abandoned. cited by applicant .
U.S. Appl. No. 16/268,721, filed Feb. 6, 2019, U.S. Pat. No.
10,846,498, Patented. cited by applicant .
U.S. Appl. No. 15/006,561, filed Jan. 26, 2016, U.S. Pat. No.
10,235,547, Patented. cited by applicant .
CN Office Action, including Search Report, dated Jan. 21, 2021 for
CN Application No. 201710140373, 11 pages. cited by applicant .
Communication about intention to grant a European patent dated Feb.
23, 2021 for EP Application No. 17151685, 5 pages. cited by
applicant .
English Translation of CN Office Action, including Search Report,
dated Jan. 21, 2021 for CN Application No. 201710140373, 14 pages.
cited by applicant .
English Translation of JP Search report dated Apr. 21, 2022 for JP
Application No. 2021053085, 21 pages. cited by applicant .
JP Search report dated Apr. 21, 2022 for JP Application No.
2021053085, 19 pages. cited by applicant .
English Translation of JP Office Action dated Jun. 1, 2022 for JP
Application No. 2021053085, 6 pages. cited by applicant .
JP Office Action dated Jun. 1, 2022 for JP Application No.
2021053085, 6 pages. cited by applicant.
|
Primary Examiner: Vallecillo; Kyle
Attorney, Agent or Firm: Alston & Bird LLP
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATIONS
The present application is a continuation of U.S. Non-Provisional
application Ser. No. 16/268,721, filed Feb. 6, 2019 (and published
Jun. 13, 2019 as U.S. Patent Application Publication No.
2019/0180068), which is a continuation of and claims the benefit of
U.S. patent application Ser. No. 15/006,561 for Enhanced Matrix
Symbol Error Correction Method filed Jan. 26, 2016 (and published
Jul. 27, 2017 as US. Patent Application Publication No.
2017/0213064), and subsequently issued as U.S. Pat. No. 10,235,547.
Each of the foregoing patent applications, patent, and patent
publications is hereby incorporated by reference in its entirety.
Claims
What is claimed is:
1. A method of error correction of a two-dimensional (2D) symbol,
the method comprising: reading, by a hardware processor, a
plurality of codewords in the 2D symbol, wherein each of the
plurality of codewords is associated with a number that is
indicative of a location of a codeword within the 2D symbol;
identifying, by the hardware processor, an optically ambiguous
codeword of the plurality of codewords in the 2D symbol, wherein
the optically ambiguous codeword corresponds to a codeword having
lowest minimum interior contrast level amongst the minimum interior
contrast level of other codewords in the plurality of codewords;
and determining, by the hardware processor, the location of the
optically ambiguous codeword based on the number associated with
the optically ambiguous codeword; and correcting, by the hardware
processor, errors in the optically ambiguous codeword based on the
location of the optically ambiguous codeword and an erroneous
decoded value associated with the optically ambiguous codeword.
2. The method of claim 1, wherein each of the plurality of
codewords comprises a plurality of cells, wherein the plurality of
cells comprises a set of space cells and a set of bar cells.
3. The method of claim 2 further comprising determining, within a
codeword of the plurality of codewords, a space cell having a
smallest space cell reflectance, and a bar cell having a largest
bar cell reflectance.
4. The method of claim 3 further comprising determining, by the
hardware processor the minimum interior contrast level associated
with the codeword based on the smallest space cell reflectance, the
bar cell having a largest bar cell reflectance, and a black/white
contrast threshold.
5. The method of claim 4 further comprising determining a
black/white contrast threshold associated with each of the codeword
based on identifying a reflectance value of the plurality of cells
in a codeword, identifying a highest reflectance value and a lowest
reflectance value amongst the reflectance value associated with
each of the plurality of cells, and determining a mean of the
highest reflectance value and the lowest reflectance value to
determine the black/white contrast threshold.
6. The method of claim 1, wherein the location of the optically
ambiguous codeword is determined independent of error correction
codewords included in the 2D symbol.
7. The method of claim 1, wherein the errors in the optically
ambiguous codeword are corrected by utilizing an error correcting
codeword.
8. An electronic device for performing error correction of a
two-dimensional (2D) symbol, the electronic device comprising: an
optical scanner configured to optically read, by an optical scanner
of a symbol reader, a plurality of codewords in the 2D symbol,
wherein each of the plurality of codewords is associated with a
number that is indicative of a location of a codeword within the 2D
symbol; a memory device configured to store an error correction
equation; a hardware processor configured to: determine a location
of a codeword of the plurality of codewords in the 2D symbol which
is optically ambiguous, wherein determining the location comprises:
performing a contrast analysis on the 2D symbol, wherein performing
of the contrast analysis comprises: identifying a respective
minimum interior contrast level for each codeword in the 2D symbol,
and flagging, as optically ambiguous, the codeword with minimum
interior contrast level that satisfies a minimum interior contrast
level criterion; determining, by the hardware processor, the
location of the optically ambiguous codeword based on the number
associated with the optically ambiguous codeword; and execute the
error correction equation based on the location of the optically
ambiguous codeword in the 2D symbol to correct an error in the
plurality of codewords.
9. The electronic device of claim 8, wherein each of the plurality
of codewords comprises a plurality of cells, wherein the plurality
of cells comprises a set of space cells and a set of bar cells.
10. The electronic device of claim 9, wherein the hardware
processor is configured to determine, within a codeword of the
plurality of codewords, a space cell having a smallest space cell
reflectance, and a bar cell having a largest bar cell
reflectance.
11. The electronic device of claim 10, wherein the hardware
processor is further configured to determine the minimum interior
contrast level associated with the codeword based on the smallest
space cell reflectance, the bar cell having a largest bar cell
reflectance, and a black/white contrast threshold.
12. The electronic device of claim 11, wherein the hardware
processor is further configured to determine a black/white contrast
threshold associated with each of the codeword based on identifying
a reflectance value of the plurality of cells in a codeword,
identifying a highest reflectance value and a lowest reflectance
value amongst the reflectance value associated with each of the
plurality of cells, and determining a mean of the highest
reflectance value and the lowest reflectance value to determine the
black/white contrast threshold.
13. The electronic device of claim 8, wherein the location of the
optically ambiguous codeword is determined independent of error
correction codewords included in the 2D symbol.
14. The electronic device of claim 8, wherein the errors in the
optically ambiguous codeword are corrected by utilizing an error
correcting codeword.
15. A computer readable, non-transitory storage medium storing
instructions that, when executed by a hardware processor of a
symbol reader, causes the hardware processor to execute a method of
error correction for a two-dimensional (2D) symbol, the method
comprises: optically reading, by an optical scanner of a symbol
reader, a plurality of codewords in the 2D symbol, wherein each of
the plurality of codewords is associated with a number that is
indicative of a location of a codeword within the 2D symbol;
determining, via a hardware processor of the symbol reader, a
location of a codeword which is optically ambiguous, the
determining comprising: performing a contrast analysis on the 2D
symbol comprising: identifying a respective minimum interior
contrast level for each codeword in the 2D symbol; and flagging, as
optically ambiguous, the codeword that has a minimum interior
contrast level below a minimum interior contrast level threshold;
and determining, by the hardware processor, the location of the
optically ambiguous codeword based on the number associated with
the optically ambiguous codeword; and executing, via the hardware
processor, an error correction equation based on the location of
the one or more optically ambiguous codewords in the 2D symbol to
correct errors in the read plurality of codewords.
16. The computer readable, non-transitory storage medium of claim
15, wherein each codeword of the plurality of codewords comprises a
plurality of cells, wherein the plurality of cells comprises a set
of space cells and a set of bar cells.
17. The computer readable, non-transitory storage medium of claim
16 further comprising determining, within a codeword of the
plurality of codewords, a space cell having a smallest space cell
reflectance, and a bar cell having a largest bar cell
reflectance.
18. The computer readable, non-transitory storage medium of claim
17 further comprising determining, by the hardware processor the
minimum interior contrast level associated with the codeword based
on the smallest space cell reflectance, the bar cell having a
largest bar cell reflectance, and a black/white contrast
threshold.
19. The computer readable, non-transitory storage medium of claim
17 further comprising determining a black/white contrast threshold
associated with each of the codeword based on identifying a
reflectance value of the plurality of cells in a codeword,
identifying a highest reflectance value and a lowest reflectance
value amongst the reflectance value associated with each of the
plurality of cells, and determining a mean of the highest
reflectance value and the lowest reflectance value to determine the
black/white contrast threshold.
20. The computer readable, non-transitory storage medium of claim
15, wherein the location of the optically ambiguous codeword is
determined independent of error correction codewords included in
the 2D symbol.
Description
FIELD OF THE INVENTION
The present invention relates to a method and apparatus for
decoding machine-readable symbols, and more particularly, to a
method and apparatus for decoding symbols requiring error
correction.
BACKGROUND
Machine-readable symbols provide a means for encoding information
in a compact printed form (or embossed form) which can be scanned
and then interpreted by an optical-based symbol detector. Such
machine readable symbols are often attached to (or impressed upon)
product packaging, food products, general consumer items, machine
parts, equipment, and other manufactured items for purposes of
machine-based identification and tracking.
One exemplary type of machine-readable symbol is a bar code that
employs a series of bars and white spaces vertically oriented along
a single row. Groups of bars and spaces correspond to a codeword.
The codeword is associated with an alpha-numeric symbol, one or
more numeric digits, or other symbol functionality.
To facilitate encoding of greater amounts of information into a
single machine-readable symbol, two-dimensional bar codes have been
devised. These are also commonly referred to as stacked, matrix
and/or area bar codes. Examples of such two-dimensional symbologies
include Data Matrix, Code One, PDF-417, MaxiCode, QR Code, and
Aztec Code. 2D matrix symbologies employ arrangements of regular
polygon-shaped cells (also called elements or modules) where the
center to center distance of adjacent elements is uniform.
Typically, the polygon-shaped cells are squares. The specific
arrangement of the cells in 2D matrix symbologies represents data
characters and/or symbology functions.
As an example of a 2D matrix symbol technology, a Data Matrix code
is a two-dimensional matrix barcode consisting of high-contrast
"cells" (typically black and white cells) or modules arranged in
either a square or rectangular pattern. The information to be
encoded can be text or numeric data, or control symbols. The usual
data size ranges from a few bytes up to 1556 bytes. Specific,
designated, standardized groups of cells--typically eight
cells--are each referred to as a "symbol character." The symbol
characters have values which are referred to as "codewords." With a
black cell interpreted as a 0 (zero) and a white cell interpreted
as a 1 (one), an eight-cell codeword can code for numbers 0 through
255; in turn, these numeric values can be associated with
alphanumeric symbols through standard codes such as ASCII, EBCDIC,
or variations thereon, or other functionality.
The codewords--that is, the designated groups of cells in a
symbol--have specific, standardized positions within the overall
symbol. The interpretation of a symbol in a given context (for
example, for a given manufacturer and/or a given product) therefore
depends on the codewords within the symbol; and in particular, the
interpretation depends on both: (i) the contents of each codeword
(that is, the pattern of cells in each codeword), and (ii) the
placement or position of each codeword in the symbol.
Typically, for sequential alphanumeric data (for example, a product
identification number or a street address), each sequential data
character is assigned to the symbols of a codeword in a
standardized order. For example, the order may be left-to-right
along the rows of the symbol, or according to a standardized
diagonal pattern of placement. Because the codewords have specific,
standards-specified placements within a symbol--and because no
information about the placement is contained in the symbol
character--the symbols may also be referred to as "matrix symbols"
or "matrix symbology barcodes."
Bar code readers are employed to read the matrix symbols using a
variety of optical scanning electronics and methods. Ideally, the
machine-readable symbols which are scanned by a bar code reader are
in perfect condition, with all of the cells of consistent, uniform
size; each cell being fully filled with either total black or total
white; and the contrast between black and white cells being
100%.
In real, practical application the machine-readable symbols which
are scanned by a bar code reader may be imperfect. They may be
smudged by external substances (grease, dirt, or other chemicals in
the environment); or the surface on which the symbols were printed
may be stretched, compressed, or torn; or the printing process
itself may be flawed (for example, due to low ink levels in a
printer, clogged printheads, etc.). The defects in actual symbols
may introduce errors in the machine reading process.
To address these practical problems, error correction techniques
are often used to increase reliability: even if one or more cells
are damaged so as to make a codeword unreadable, the unreadable
codeword can be recovered through the error-correction process, and
the overall message of the symbol can still be read.
For example, machine-readable symbols based on the Data Matrix ECC
200 standard employ Reed-Solomon codes for error and erasure
recovery. ECC 200 allows the routine reconstruction of the entire
encoded data string when the symbol has sustained 25% damage
(assuming the matrix can still be accurately located).
Under this standard, approximately half the codewords in a symbol
are used directly for the data to be represented, and approximately
half the codewords are used for error correction. The
error-correction (EC) symbols are calculated using a mathematical
tool known as the Reed-Solomon algorithm. The codewords for the
symbol are the input to the Reed-Solomon algorithm, and the
error-correction (EC) symbols are the output of the Reed-Solomon
algorithm. The complete machine-readable symbol includes both the
data codewords and the EC codewords.
For a given symbol format (such as Data Matrix, PDF-417, QR-Code,
Aztec Code, and others), and for a given size of the symbol matrix,
there are a fixed, designated numbers of EC codewords. To recover
any one, particular damaged (unreadable) codeword, two things must
be recovered: (i) the location of the damaged data codeword within
the symbol, and (ii) the contents (the bit pattern) of the damaged
data codeword. In turn, to recover both the location and the bit
pattern for a single codeword requires two of the available EC
symbols. It follows that if a machine-readable symbol has two
damaged codewords, four EC codewords are required to recover the
full symbol. Generally, if a symbol has "N" damaged codewords, then
2*N EC codewords are required to recover the full symbol.
The number of EC codewords in a symbol is limited. This places a
limit on the number of damaged, unreadable data codewords which can
be recovered. Generally, with error correction techniques, and
using present methods, the number of damaged data codewords which
can be recovered is half the total number of EC codewords. For
example, in a Data Matrix symbol with 16.times.16 cells, the total
number of EC codewords is 12. This means that at most 6 damaged
data codewords can be recovered. If more than 6 of the data
codewords are damaged, the complete symbol may be unreadable.
However, if the location of the data codeword in error is already
known, then only one EC codeword is needed to correct the error.
This technique is called "erasure decoding". Unfortunately, in
Matrix Code symbols generally, the location of the errors is not
known.
Therefore, there exists a need for a system and method for
recovering more damaged data codewords in a symbol than may be
recovered based on only the error-correcting symbols by themselves.
More particularly, what is needed is a system and method for
determining the location of a damaged or erroneous data codeword,
independent of the information stored in the EC codewords.
SUMMARY
Accordingly, in one aspect, the present invention solves the
problem of not being able to use erasure decoding with matrix
symbologies by evaluating the gray-level information available in
the scanner and keeping track of those codewords with the least
contrast difference. The decoder then utilizes erasure decoding on
these least-contrast codewords. Since the location of the erroneous
data codewords has been estimated via the contrast detection, only
one EC codeword is required to recover the data in the damaged
codeword. (And so, only one EC codeword is required to fully
recover the damaged data codeword, both its location and data.)
Because only one EC codeword is required instead of two, more EC
codewords remain unused and available for decoding other possible
errors. This increases the total number of data codewords that can
be corrected. This is particularly useful in applications where
symbols get dirty (e.g. automotive assembly), damaged (e.g. supply
chain), have specular components (e.g. direct part marking (DPM))
and need to be scanned over a greater range (e.g. all
applications).
The algorithm of the present invention has the effect of nearly
doubling the number of codewords that can be corrected in matrix
symbology decodes, thereby greatly improving the performance over
what is currently available.
The foregoing illustrative summary, as well as other exemplary
objectives and/or advantages of the invention, and the manner in
which the same are accomplished, are further explained within the
following detailed description and its accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a perspective view of an exemplary hand-held symbol
reader acquiring data from a machine-readable symbol.
FIG. 2 is an internal block diagram of an exemplary symbol reader
for acquiring data from a machine-readable symbol
FIG. 3 illustrates several exemplary machine-readable 2D
symbols.
FIG. 4 provides two views of an exemplary 2D symbol which is
damaged.
FIG. 5 is a flow-chart of an exemplary method for optically
enhanced Reed-Solomon error-correction for a 2D symbol.
FIG. 6 is a flow-chart of an exemplary method for contrast analysis
for a 2D symbol as part of enhanced Reed-Solomon error
correction.
FIG. 7 presents an exemplary array of codeword contrast values used
for enhanced error correction by applying contrast analysis to a
flawed codeword.
FIG. 8 illustrates an exemplary case-study of enhanced error
correction by applying contrast analysis to a flawed codeword.
DETAILED DESCRIPTION
In the following description, certain specific details are set
forth in order to provide a thorough understanding of various
embodiments. However, one skilled in the art will understand that
the invention may be practiced without these details. In other
instances, well-known structures associated with imagers, scanners,
and/or other devices operable to read machine-readable symbols have
not been shown or described in detail to avoid unnecessarily
obscuring descriptions of the embodiments.
Unless the context requires otherwise, throughout the specification
and claims which follow, the word "comprise" and variations
thereof, such as, "comprises" and "comprising" are to be construed
in an open sense, that is as "including, but not limited to."
Reference throughout this specification to "one embodiment" or "an
embodiment" means that a particular feature, structure or
characteristic described in connection with the embodiment is
included in at least one embodiment. Thus, the appearances of the
phrases "in one embodiment" or "in an embodiment" in various places
throughout this specification are not necessarily all referring to
the same embodiment. Furthermore, the particular features,
structures, or characteristics may be combined in any suitable
manner in one or more embodiments.
The headings provided herein are for convenience only and do not
interpret the scope or meaning of the claimed invention.
Symbol Reader
The present system and method embrace devices designed to read
machine-readable symbols.
In an exemplary embodiment, such a device may be a hand-held
scanner. FIG. 1 is a perspective view of an exemplary hand-held
symbol reader 100 acquiring data from a machine-readable symbol
102.
The machine-readable symbol 102 is affixed to a package 104 or the
like such that the user points the hand-held symbol reader 100
towards the machine-readable symbol 102. The symbol reader 100 may
be a line scanner operable to emit and sweep a narrow beam of
electromagnetic energy across a field-of-view 106 over
two-dimensional (2D) machine-readable symbol 102. In other
embodiments, an aperture means, mirror, lens or the like is
adjusted to sweep across a symbol line to receive returning
electromagnetic energy from a relatively small portion (e.g., cell)
of the machine-readable symbol, which is detected by an optical
detector system.
In yet other embodiments, a 2D array symbol reader acquires a
captured image of the machine-readable symbol (and a suitable
region of quiet area around the machine-readable symbol). For the
present system and method, which relies upon a contrast analysis of
the cells within the symbol 102, the acquisition of a captured
image of the symbol may be a preferred method of operation for the
symbol reader 100. Suitable image processing hardware 235 and
software running on processors 242, 244 are used to deconstruct the
capture image to determine the data bits represented by the cells,
and to perform the contrast analysis of the present system and
method (see FIG. 2 below).
The machine-readable symbol reader 100 is illustrated as having a
housing 108, a display 110, a keypad 112, and an actuator device
114. Actuator device 114 may be a trigger, button, or other
suitable actuator operable by the user to initiate the symbol
reading process.
The machine-readable symbol 102 shown in the figure is intended to
be generic and, thus, is illustrative of the various types and
formats of machine-readable symbols. For example, some
machine-readable symbols may consist of a single row of codewords
(e.g., barcode). Other types of machine-readable symbols (e.g.,
matrix or area code) may be configured in other shapes, such as
circles, hexagons, rectangles, squares and the like. It is intended
that many various types and formats of machine-readable symbologies
be included within the scope of the present system and method.
Symbol Reader Internal Block Diagram
An internal block diagram of an exemplary symbol reader 100 of a
type which may implement the present system and method is shown in
FIG. 2.
In one embodiment of the present system and method, the symbol
reader 100 may be an optical reader. Optical reader 100 may include
an illumination assembly 220 for illuminating a target object T,
such as a 1D or 2D bar code symbol 102, and an imaging assembly 230
for receiving an image of object T and generating an electrical
output signal indicative of the data which is optically encoded
therein. Illumination assembly 220 may, for example, include an
illumination source assembly 222, such as one or more LEDs,
together with an illuminating optics assembly 224, such as one or
more reflectors, for directing light from light source 222 in the
direction of target object T. Illumination assembly 220 may be
eliminated if ambient light levels are certain to be high enough to
allow high quality images of object T to be taken.
In an embodiment, imaging assembly 230 may include an image sensor
232, such as a 2D CCD or CMOS solid state image sensor, together
with an imaging optics assembly 234 for receiving and focusing an
image of object T onto image sensor 32. The array-based imaging
assembly shown in FIG. 2 may be replaced by a laser scanning based
imaging assembly comprising a laser source, a scanning mechanism,
emit and receive optics, a photodetector and accompanying signal
processing circuitry. The field of view of the imaging assembly 230
will depend on the application. In general, the field of view
should be large enough so that the imaging assembly can capture a
bit map representation of a scene including an image data reading
region at close reading range.
In an embodiment of the present system and method, exemplary symbol
reader 100 of FIG. 2 also includes programmable controller 240
which may comprise an integrated circuit microprocessor 242 and an
application specific integrated circuit (ASIC) 244. Processor 242
and ASIC 244 are both programmable control devices which are able
to receive, output and process data in accordance with a stored
program stored in either or both of a read/write random access
memory (RAM) 245 and an erasable read only memory (EROM) 246.
Processor 242 and ASIC 244 are also both connected to a common bus
248 through which program data and working data, including address
data, may be received and transmitted in either direction to any
circuitry that is also connected thereto. Processor 242 and ASIC
244 may differ from one another, however, in how they are made and
how they are used.
In one embodiment, processor 242 may be a general purpose,
off-the-shelf VLSI integrated circuit microprocessor which has
overall control of the circuitry of FIG. 2, but which devotes most
of its time to decoding image data stored in RAM 245 in accordance
with program data stored in EROM 246. Processor 244, on the other
hand, may be a special purpose VLSI integrated circuit, such as a
programmable logic or gate array, which is programmed to devote its
time to functions other than decoding image data, and thereby
relieve processor 242 from the burden of performing these
functions.
In an alternative embodiment, special purpose processor 244 may be
eliminated entirely if general purpose processor 242 is fast enough
and powerful enough to perform all of the functions contemplated by
the present system and method. It will, therefore, be understood
that neither the number of processors used, nor the division of
labor there between, is of any fundamental significance for
purposes of the present system and method.
In an embodiment, exemplary symbol reader 100 includes a signal
processor 235 and an analog-to-digital (A/D) chip 236. These chips
together take the raw data from image sensor 232 and convert the
data to digital format, which in an exemplary embodiment may be a
gray-level digital format, for further processing by programmable
controller 240.
In an embodiment, the system and method of the present invention
employs algorithms stored in EROM 246 which enable the programmable
controller 240 to analyze the image data from signal processor 235
and A/D 236. In an embodiment, and as described further below, this
image analysis may include analyzing gray-level information
(contrast levels) in the image data. In an embodiment, and in part
based on the contrast level analysis, programmable controller 240
may then implement an improved system and method of error
correction for matrix symbols by relying on optical contrast-level
analysis, as also described further below.
Exemplary symbol reader 100 may also include input/output (I/O)
circuitry 237, for example to support the use of the keyboard 112
and trigger 114. Symbol reader 100 may also include output/display
circuitry 238 to support display 110.
Exemplary Symbols
FIG. 3 illustrates several exemplary machine-readable 2D symbols
102 labeled 102.1 and 102.2.
Symbol 102.1 is an exemplary machine-readable symbol encoded
according to the Data Matrix barcode (ECC 200) standard. The symbol
102.1, which is a 24.times.24 array, has two solid black borders
302 forming an "L-shape" which are the finder pattern, enabling the
symbol reader to determine the location and orientation of the 2D
symbol. The symbol also has two opposing borders of alternating
dark and light cells which form a "timing pattern" 304 which help
the symbol reader identify the size (the number of rows and
columns) of the symbol.
Interior to the finder pattern 302 and timing pattern 304 are rows
and columns of interior cells 306 which encode information. As may
be evident from the figure, an ideal machine-readable symbol has a
very high contrast level between the first color dark cells and the
second color light cells, in many cases achieved by employing
clearly printed, unobscured cells which are either all black or all
white.
Symbol 102.2 is an exemplary 16.times.16 machine-readable symbol
encoded according to the Data Matrix barcode (ECC 200) standard. In
symbol 102.2, and for purposes of illustration only, the interior
black data cells are omitted, and boundaries between the interior
cells 306 are suggested by shaded, dotted lines which are not
normally present in actual printed data matrix symbols.
Also, not normally present in actual printed symbols, but included
here for purposes of illustration, are solid borders which indicate
the boundaries of the codewords 308 formed by the interior cells
306. In an embodiment, each codeword 308 is composed of eight cells
representing a single byte of data. It will be seen that there are
several types of codewords, including data codewords 308.1 which
encode the actual data to be represented by the symbol;
error-correcting (EC) codewords 308.2 which are generated from the
data codewords according to the Reed-Solomon algorithm; and padding
codewords 308.3.
The figure also identifies one exemplary bar (black) cell 306.B and
one exemplary space (white) cell 306.S.
The illustration here of machine-readable symbols based on the Data
Matrix barcode standard, as well as the size, shape, and data
contents illustrated, are exemplary only and should not be
construed as limiting. The present system and method are applicable
to a wide variety of 2D matrix barcodes according to a variety of
known standards, as well as being applicable to other 2D
machine-readable symbols which may be envisioned in the future.
Symbol Errors
As discussed above, the data content of symbols 102 is stored or
presented in the form of cells 306 of contrasting colors within
codewords 308. In an embodiment of the present system and method,
the light cells (typically white) represent ones (1's) and the dark
cells (typically black) represent zeros (0's). In an alternative
embodiment, a light cell represents zero (0) and the dark cells
represent (1). In alternative embodiments, other colors or levels
of shading may be employed. As a general matter, however, for the
coding to be effective the symbol reader 100 must be readily able
to distinguish the dark cells from the light cells. Also, the data
is stored not only in terms of the cells 306 per se, but also in
terms of the positions of the cells 306 within the codewords 308,
and the positions of each codeword 308 within the symbol 102.
If a symbol 102 is damaged, there may be insufficient contrast
between light cells and dark cells for the symbol reader 100 to
reliable distinguish the cells. Similarly, damage to the symbol may
render it difficult for the symbol reader to identify the location
or boundaries of cells 306 and codewords 308. In other cases,
damage to cells 306 can cause a change from black to white or
vice-versa. This in turn calls upon the error-correction methods,
such as Reed-Solomon, already discussed above. The present system
and method are intended to augment Reed-Solomon and similar
error-correction methods with information based on contrast
analysis.
FIG. 4 provides two views 102.D1, 102.D2 of an exemplary symbol
which is damaged, so that the original high-contrast has been lost
while the symbol 102 is in use in the field.
In the first view, the damaged symbol 102.D1 shown in the figure
was photographed in a real-world automotive manufacturing plant. It
is apparent that there is a dark vertical scuff mark 402 which is
approximately down the middle of the symbol 102.D1. The scuffing is
sufficiently dark that, when read with a standard symbol reader
100, the reader 100 mistakes many individual cells 306 for black
when (as printed, and without damage or scuffing) they are white
cells. This in turns causes codeword errors. This symbol 102.D1
will not read with current scanners.
The actual value of the codewords in symbol 102.D1 is listed here
(codewords before the colon are data codewords, those after the
colon are error-correction codewords):
237 151 230 204 27 207 144 165 112 27 13 43 222 60 125 34 137 186
71 163 223 254:96 9 171 31 209 21 131 100 111 146 225 95 109 112
182 218 118 203
The values for the codewords determined by a symbol reader 100 are
shown here, with the incorrect codewords underlined:
237 151 230 204 27 207 144 165 112 27 173 111 222 60 125 34 137 191
127 235 223 254:96 25 175 191 208 21 131 100 111 146 225 95 111 116
182 218 118 203
As is apparent in the image of symbol 102.D1, throughout the
smudged region 402 the contrast between many individual cells is
small, and is close to the threshold level between black and white.
Compare for example a cluster of low contrast cells 404 within the
smudged region 402 with a non-damaged, machine-readable high
contrast region 406.
In the second view, the damaged symbol 102.D2 is illustrated as it
was interpreted by an actual scanner 100 in the field. As shown by
the codewords with shaded cells 306 in the illustration, there were
eleven codewords 308 which provided flawed readings from the
scanner 100, and may be described as flawed codewords 308.F.
Erasure Vs. Error:
By way of terminology, it is noted here that if the position of an
erroneous codeword is known, but the data is not known (or is
ambiguous), the codeword is referred to as an "erasure." If the
data of an erroneous codeword is unknown and the position of the
codeword is also unknown, the codeword is referred to as an
"error."
Reed-Solomon Error Correction
In an embodiment, the present system and method includes
application of error-correcting codes and analyses, augmented with
optical analysis of a machine-readable symbol 102, to detect and
correct errors in the machine-readable symbol 102. Various
mathematical methods of error correction are well-known in the art,
and a detailed description is beyond the scope of this document.
However, review of a few basic elements of an exemplary
error-correction method may aid in the understanding of the present
system and method.
All standardized 2D matrix symbologies utilize the Reed-Solomon
methodology. In Reed-Solomon codes, a set of data elements, such as
bytes of data, may be redundantly encoded in a second set of
error-correcting elements (also typically in byte form), which for
present purposes can be referred to as EC codewords 308.2. The
error-correcting codewords are transmitted or presented along with
the principle data elements, enabling reconstruction of damaged
data elements.
Methods of constructing the Reed-Solomon EC codewords (based on a
given, particular data set) are outside the scope of this document.
It suffices for present purposes to understand that
Reed-Solomon-derived EC codewords 308.2 can be calculated, and the
resulting EC codewords are included as part of 2D matrix symbols,
as already described above.
There are a variety of methods of decoding a message with
Reed-Solomon error correction. In one exemplary method, the values
of the data codewords 308.1 of a symbol 102 are viewed as the
coefficients of a polynomial s(x) that is subject to certain
constraints (not discussed here):
.function..times..times. ##EQU00001##
It will be noted that not only the values of the data codewords
308.1 matter, but also their order. The ordinal placement of the
codewords (1.sup.st, 2.sup.nd, 3.sup.rd, etc.) in the polynomial
maps to the physical ordering of the data codewords 308.1 in the
machine-readable symbol 102.
If the machine-readable symbol 102 is damaged or corrupted, this
may result in data codewords 308.1 which are incorrect. The
erroneous data can be understood as a received polynomial r(x):
.function..function..function. ##EQU00002##
.function..times..times. ##EQU00002.2##
where e.sub.i is the coefficient for the i.sup.th power of x.
Coefficient e.sub.i will be zero if there is no error at that power
of x (and so no error for the corresponding i.sup.th data codeword
308.1 in the symbol 102); while the coefficient e.sub.i will be
nonzero if there is an error. If there are .nu. errors at distinct
powers i.sub.k of x, then:
.function..times..times..times..times. ##EQU00003##
The goal of the decoder is to find the number of errors (.nu.), the
positions of the errors (i.sub.k), and the error values at those
positions (e_i.sub.k). From those, e(x) can be calculated, and then
e(x) can be subtracted from the received r(x) to get the original
message s(x).
There are various algorithms which can be employed, as part of the
Reed-Solomon scheme, to identify the error positions (i.sub.k) and
the error values at those positions (e_i.sub.k), based solely on
the received data codewords 308.1 and the received EC codewords
308.2. The processes involved, however, are generally a two-stage
processes, where:
Stage (I) Error Locations:
The first calculation stage entails identifying the location of the
errors. This entails first calculating an error-locator polynomial
.LAMBDA., and based on .LAMBDA., calculating the non-zero error
positions i.sub.k. This stage also determines the number of errors
(.nu.). This first stage calculation inevitably requires the use of
some of the EC codewords 308.2 in the symbol 102.
Stage (II) Corrected Values:
Employing the location errors i.sub.k as calculated in stage (i),
the second calculation stage identifies the correct values
(e_i.sub.k) associated with each error location.
It will be seen then that in the prior art, correcting errors is a
two-stage process, where identifying error locations generally
precedes, and is an input to, identifying the corrected data at
each location. It is a goal of the present system and method to
either reduce or possibly eliminate the calculations of stage (I),
by using analyses apart from Reed-Solomon error correction to
determine identify or mark the erroneous data codewords 308.1.
Persons skilled in the art will recognize that the non-zero error
positions i.sub.k calculated via the alternative methods (discussed
further below) can be input directly into stage (II), thereby
enabling the calculations of the correct data values in stage
(II).
Importantly, in the mathematics of standard Reed-Solomon error
correction, errors (both location and data unknown) requires the
use of two error correcting code words to repair a damaged
codeword. If, on the other hand, knowledge of the location of the
error exists, then the error is considered an erasure, and only one
error correction codeword is required to repair the erased
codeword.
Stated another way: Normally, error-correction in 2D matrix
symbologies is used to correct codewords which are errors, meaning
that both the location and contents of the codeword are unknown.
The goal of the present system and method is to independently flag
errors so that they are instead treated as erasures, for which the
location is known, thereby requiring only one EC codeword for
correction.
Optical Clarity and Optical Ambiguity, Decoding Disadvantage, and
Reed-Solomon Error Correction
As discussed above, Reed-Solomon error correction requires the use
of two EC codewords 308.2 to correctly recover both the location
and the data contents of a single data codeword 308.1 which is
flawed. However, the present system and method aims to enable the
identification (at least provisionally) of the locations of the
flawed or damaged codewords 308.F--and to make such identification
independently of the EC codewords 308.2 in the symbol 102. Such
alternative means of locating the data codewords 308.1 which are
flawed supplements the data in the EC codewords 308.2; as a result,
only a single EC codeword 308.2 is required to identify the data in
a data codeword 308.1 Flawed codewords 308.F may also be referred
to as codewords which have a "decoding disadvantage."
To identify the locations of the codewords with a decoding
disadvantage, independent of the error-correcting information
within the symbol 102 itself, the present system and method
identifies those codewords 308 in the symbol 102 which have a low
level of optical clarity, or equivalently, a high level of optical
ambiguity. By "optical clarity" is meant any codeword 308 which, as
presented to the reader 100, is sufficiently clear and distinct
(e.g., has high optical contrast) to be read very reliably by the
symbol reader's optical system 230, 235. If a codeword 308 is not
optically clear--for example, due to poor printing, smudging or
marking in the field, ripping or tearing, or other causes--then the
codeword is deemed optically ambiguous; there is a significant
probability that the data for an optically ambiguous codeword, as
determined by a reader 100, will not match the intended data of the
same codeword.
FIG. 5 presents a flow-chart of an exemplary method 500 for
optically enhanced Reed-Solomon error-correction for a symbol 102.
The steps of exemplary method 500 are generally performed via the
processor(s) 240, memory 245, and other components of the symbol
reader 100.
In step 505, the symbol reader 100 identifies the location of the
symbol 102 and the appropriate parameters such as the size. For
example, for a DataMatrix symbol, the reader 100 finds the
"L-shape" 302 and finds the clock track 304 to identify the number
of rows and columns in the symbol. The L-shape 302 and clock track
304 help the reader 100 determine the symbol's tilt and
orientation, and provide reference points from which to decode the
matrix of data cells.
In step 510, the symbol reader 100 creates a matrix or array of
sample points (pixels), indicating the reflectances (bright or
dark) of points within the symbol 102. These sample points are used
to determine reflectance of cells 306 within the symbol. A single
cell 306 may have multiple sample points measured, and together
these may be used (for example, averaged) to determine the
reflectance of each cell 306.
As discussed above, the symbol 102 is composed of codewords 308
with standardized positions, that is, which are made up of
standardized clusters of cells 306 with designated positions within
the symbol matrix 102.
In step 515, the method 500 determines a level of optical clarity
for each codeword 308. A high level of optical clarity, which is
desirable, means the codeword's cells are distinctive and that the
data value of the codeword can be read with a high probability of
accuracy.
A low level of optical clarity--or equivalently, a high level of
optical ambiguity--may result from physical damage to a symbol, or
from dirt or grease marking the symbol, or other causes as
discussed above. Low optical clarity, or high optical ambiguity,
means that the codeword's cells are not distinctive and the
codeword has a decoding disadvantage. The low level of optical
clarity therefore means that the data value of the codeword can be
ascertained only with a suboptimal degree of reliability.
Optical clarity/ambiguity may be determined in a variety of ways.
In one embodiment of the present system and method, discussed in
detail below, the optical clarity/ambiguity is determined based on
an analysis of the contrast level between cells 306 within each
codeword 308. Codewords 306 which exhibit the lowest internal
contrast levels may be marked as optically ambiguous.
In an alternative embodiment, optical clarity/ambiguity may be
determined based on analysis of the degree to which a codeword 308
is in-focus or not in-focus. In an alternative embodiment, optical
clarity/ambiguity may be determined based on analysis of the
definition or lack of definition of lines separating the dark cells
306 from light cells 306.
In an alternative embodiment, optical clarity/ambiguity may be
determined based on a degree to which the horizontal and vertical
lines of the codewords 308 are parallel to, or are not parallel to,
the border-L shape. Other methods of assessing optical clarity of a
codeword 308 may be envisioned as well, and fall within the scope
and spirit of the present system and method.
In step 520, exemplary method 500 ranks the codewords 308 according
to optical clarity, for example from highest to lowest in optical
clarity. In step 525, method 500 identifies the lowest ranked
codewords (those which are most optically ambiguous), up to the
number of codewords 308 to be used as erasures.
In steps 530 and 535, the lowest-ranked codewords 308 identified in
step 525--that is, the codewords with the highest optical
ambiguity--are marked as erasures in the error-correction
equations, and the Reed-Solomon error-correction equations are then
executed. Steps 530 and 535 thereby reduce or eliminate the
calculations discussed above for a phase (I) of the Reed-Solomon
error correction process, and thereby also reduce or eliminate the
use of EC codewords 308.2 to identify the locations of flawed
codewords 308.F.
Gray-Scale Contrast Analysis Algorithm
In one embodiment, the present system and method identifies
codewords 308 with high optical ambiguity (low optical clarity) via
contrast analysis of the codewords within the symbol 102.
The present system and method employ a "matrix-cell contrast
analysis algorithm," "gray-scale contrast analysis algorithm," or
simply "contrast analysis algorithm" (CAA) for short. The contrast
analysis algorithm of the present system and method determines the
actual gray level of each cell 306 in the symbol 102. The CAA also
identifies the black/white contrast threshold for the symbol 102.
The black/white contrast threshold is the brightness level above
which a cell 306 is considered to be white, and below which a cell
is considered to be black. The algorithm then determines the
difference between the contrast level of each cell 306 and the
black/white threshold. If the differential is comparatively low for
one or more cells 306 in a particular codeword 308, the codeword
306 may have a decoding disadvantage.
More generally, the CAA may identify a light/dark threshold level,
which is a brightness level above which a cell 306 is considered to
be of a first, lighter color (for example, white); and below which
a cell is considered to be of a second, darker color (for example,
black).
A scanner 100 will conventionally store, in memory 245, the "color"
of each cell 306, for example, a red-green-blue (RGB) value or a
hue-saturation-brightness (HSB) value. The present system and
method will also store, in the memory (245) of the scanner 100, an
actual, measured gray-scale level for each cell 306.
FIG. 6 presents a flow-chart of an exemplary method 600 for
contrast analysis according to the present system and method. Steps
605 through 645 of exemplary method 600 collectively may be
considered to be one exemplary embodiments of step 515 of method
500, already discussed above. (Step 515 determines an optical
clarity for each codeword 308 in the symbol 102.) Step 650 of
exemplary method 600 may be considered to be one exemplary
embodiment of step 520 of method 500, that is, ranking the
codewords for optical clarity.
Where exemplary method 500 was directed to generally determining
and ranking codewords 308 by optical clarity, the exemplary method
600 particularly employs an exemplary approach to contrast analysis
in order to determine and rank optical clarity. The steps of
exemplary method 600 are generally performed via the processor(s)
240, memory 245, and other components of the symbol reader 100.
In step 605, the symbol reader 100 determines a local black/white
contrast threshold (BWCT). The black/white contrast threshold
(BWCT), as described above, is a reflectance level above which a
cell 306 is considered white, and below which a cell 306 is
considered black. This is typically determined by (i) identifying
the reflectance of all the cells 306 in the symbol; (ii)
identifying the highest reflectance value and the lowest
reflectance value; and (iii) identifying a middle-value, such as
the mean or the median, and using the middle-value as the BWCT. The
present system and method refine this by employing a local BWCT for
each cell 306. In an exemplary embodiment, a local BWCT for a given
cell 306 may be determined by considering only those other cells
local to the given cell 306, and then identifying the mean or
median reflectance among those cells. In an embodiment, the number
of local cells used to determine the local BWCT may be twenty (20).
In an alternative embodiment the number of local cells used to
determine the BWCT for a given cell may be higher or lower than
twenty (20).
In step 610, the method 600 selects a particular codeword 308, (as
specified in the appropriate standards for the size and shape of
the symbol 102), and identifies the contrast level (the grayscale
level) of each cell in the codeword.
In step 615, the method 600 determines, for the particular codeword
at hand, a bar cell (306.B) with a contrast value closest to the
BWCT; and a space cell (306.S) with a contrast value closest to the
BWCT; and then stores these two cell contrast values in a codeword
contrast values array in memory (see FIG. 7 below for an example).
The contrast values may be labeled as RSmin for the space cell
(306.S) closest to the BWCT, and RBmax for the bar cell (306.B)
closest to the BWCT. An equivalent phrasing: RSmin is the smallest
space cell reflectance (darkest), and RBmax is the largest bar cell
reflectance (lightest).
Steps 610 and 615 are repeated for all codewords 308 in the symbol
102. This results in a listing of RSmin and RBmax for each codeword
308 in the symbol.
In step 620, the method 600 determines the erasure gap for spaces
between RSmin and the local black/white contrast threshold for each
codeword. (ESgap=RSmin-localBWCT)
In step 625, the method 600 determines the erasure gap for bars
between RBmax and the local black/white contrast threshold for each
codeword. (EBgap=localBWCT-RBmax)
In step 630, the method 600 identifies the largest space cell value
in the entire array, that is the largest value for RSmin. This
value, which may be labeled as RSmm, is used for normalization in
the following step.
In step 635, the method 600 divides all space gap value entries
(ESgap) by the largest space cell ("white cell") value in the
array, RSmm, generating an Sgap % value for each codeword. (Sgap
%=ESgap/RSmm)
In step 640, the method 600 identifies the largest bar cell ("black
cell") value in the entire array, that is the largest value for
RBmin. This value, which may be labeled as RBmm, is used for
normalization in the following step.
In step 645, the method 600 divides all bar gap value entries
(EBgap) by the largest bar cell value in the array, RBmm,
generating a Bgap % value for each codeword. (Bgap
%=EBgap/RBmm)
Sgap % and Bgap %, then, are the percentage relative closeness of
the deviant cell to the black/white contrast threshold. These
percentage values, Sgap % and Bgap %, may also be referred to as
the minimum interior contrast levels 702 for each cell 306. The
minimum interior contrast levels 702 are a measure of the optical
clarity of the codewords 308 in the symbol 102. Specifically: Those
codewords 308 with the lowest values for Sgap % and/or the lowest
values for Bgap % have the highest optical ambiguity (and therefore
the least or worst optical clarity).
As noted above, the preceding steps 605 through 645 of method 600
may collectively be considered to be one exemplary embodiment of
step 515 of method 500, already discussed above, that is,
determining an optical clarity for each codeword 308 in the symbol
102.
In step 650, and based on the Sgap % and Bgap % values determined
in steps 635 and 645, the method 600 ranks the lowest gap percent
values up to the number of error correction codewords to be used as
erasures. Step 650 of exemplary method 600 may be considered to be
one exemplary embodiment of step 520 of method 500, that is,
ranking the codewords for optical clarity/ambiguity.
These lowest ranked, least clear codewords are the codewords with
the lowest optical clarity (or highest ambiguity), which are then
used as erasures in the Reed-Solomon equations (step 530 of method
500).
Sample Applications
FIG. 7 presents an exemplary codeword contrast values array 700 of
the kind which may be constructed according to exemplary method
600, above. The array contains actual codeword measurements for the
symbol image 102.D1/102.D2 of FIG. 4, above. In array 700, CW is
the codeword number; and, as per discussion above: RSmin is the
smallest (darkest) space cell reflectance for each codeword 308;
RBmax is the largest (lightest) bar cell reflectance for each
codeword 308; ESgap is the erasure space gap calculated as RSmin
minus the threshold (75 hex in this case); EBgap is the threshold
minus RBmax for the bar cells; Sgap % and Bgap % are the relative
closeness of the deviant cell to the black/white threshold in
percent, also referred to as the minimum interior contrast levels
702; and Rank is a listing of the worst 12 codewords (those with
the smallest gap percentage) in the symbol 102.
FIG. 8 illustrates an exemplary case-analysis demonstrating how
poor cell contrast can identify a majority of flawed codewords
308.F. The damaged symbols shown in the figure are the same as the
damaged symbol pictured and illustrated in FIG. 4, above. In FIG.
8, numbered codeword locations 805 are identified (by a
standardized number scheme) for those codewords which are flowed or
damaged.
102.D2, reproduced here from FIG. 4 for convenience, is the damaged
symbol as it was interpreted by an actual scanner 100 in the
field.
Symbol 102.D3 is the same symbol as it was interpreted according
the exemplary contrast analysis algorithms discussed above in
conjunction with FIG. 5 and FIG. 6.
As can be seen in FIG. 8, there are two codewords 815 which were
assessed as being in error by the present system and method, but
which were actually read correctly by the scanner 100. Of the
latter codewords, one was in the damaged region 402 (codeword 27)
and another was a codeword where there is a scratch through the
dark cell, making it lighter (codeword 22).
As can also be seen from FIG. 8, there is one codeword 810 which
was actually read in error by the scanner 100, but was not flagged
by the gray-scale contrast analysis algorithm of the present system
and method.
All the remaining, identified codewords 308 (a total of ten) which
were flagged as being in error based on contrast analysis are
codewords which were, in fact, read in error by the scanner
100.
The codeword that the analysis missed (codeword 27) is easily
decoded using the 6 error correction codewords still remaining.
This is an example of a symbol that was far from being decodable
using standard decoding methods, yet using a gray-scale contrast
analysis algorithm, the symbol can sustain this and slightly more
damage and still be decodable.
Further Applications
The example shown (in FIGS. 4 and 8) clearly benefits from the
gray-scale contrast analysis decoding since the damage to the
symbol 102.D1/102.D2 is contrast based. However, the present system
and method will also work with other types of damage such as matrix
distortion, uniform dark or light damage and for DPM cell
variation. When these types of distortion are present, there will
be many sample points that rest on cell boundaries which will be
recorded as reduced contrast values. As long as the matrix
distortion (such as wrinkling) is localized or the dark/light
damage is less than approximately one-third of the symbol, the
present system and method will substantially improve decoding rates
on all types of problem symbols 102.D.
SUMMARY
Improved matrix symbology decode performance is possible when there
is some knowledge of potentially damaged codewords 308. One means
of achieving improved decode performance is by measuring the
gray-level contrast variation of every codeword, and marking those
with contrast values that are closest to the black/white threshold
as erasures. Using gray-level information and using erasure
correction in matrix symbologies will allow successful decoding far
into a damage region where current product decoding fails.
To supplement the present disclosure, this application incorporates
entirely by reference the following patents, patent application
publications, and patent applications: U.S. Pat. Nos. 6,832,725;
7,128,266; U.S. Pat. Nos. 7,159,783; 7,413,127; U.S. Pat. Nos.
7,726,575; 8,294,969; U.S. Pat. Nos. 8,317,105; 8,322,622; U.S.
Pat. Nos. 8,366,005; 8,371,507; U.S. Pat. Nos. 8,376,233;
8,381,979; U.S. Pat. Nos. 8,390,909; 8,408,464; U.S. Pat. Nos.
8,408,468; 8,408,469; U.S. Pat. Nos. 8,424,768; 8,448,863; U.S.
Pat. Nos. 8,457,013; 8,459,557; U.S. Pat. Nos. 8,469,272;
8,474,712; U.S. Pat. Nos. 8,479,992; 8,490,877; U.S. Pat. Nos.
8,517,271; 8,523,076; U.S. Pat. Nos. 8,528,818; 8,544,737; U.S.
Pat. Nos. 8,548,242; 8,548,420; U.S. Pat. Nos. 8,550,335;
8,550,354; U.S. Pat. Nos. 8,550,357; 8,556,174; U.S. Pat. Nos.
8,556,176; 8,556,177; U.S. Pat. Nos. 8,559,767; 8,599,957; U.S.
Pat. Nos. 8,561,895; 8,561,903; U.S. Pat. Nos. 8,561,905;
8,565,107; U.S. Pat. Nos. 8,571,307; 8,579,200; U.S. Pat. Nos.
8,583,924; 8,584,945; U.S. Pat. Nos. 8,587,595; 8,587,697; U.S.
Pat. Nos. 8,588,869; 8,590,789; U.S. Pat. Nos. 8,596,539;
8,596,542; U.S. Pat. Nos. 8,596,543; 8,599,271; U.S. Pat. Nos.
8,599,957; 8,600,158; U.S. Pat. Nos. 8,600,167; 8,602,309; U.S.
Pat. Nos. 8,608,053; 8,608,071; U.S. Pat. Nos. 8,611,309;
8,615,487; U.S. Pat. Nos. 8,616,454; 8,621,123; U.S. Pat. Nos.
8,622,303; 8,628,013; U.S. Pat. Nos. 8,628,015; 8,628,016; U.S.
Pat. Nos. 8,629,926; 8,630,491; U.S. Pat. Nos. 8,635,309;
8,636,200; U.S. Pat. Nos. 8,636,212; 8,636,215; U.S. Pat. Nos.
8,636,224; 8,638,806; U.S. Pat. Nos. 8,640,958; 8,640,960; U.S.
Pat. Nos. 8,643,717; 8,646,692; U.S. Pat. Nos. 8,646,694;
8,657,200; U.S. Pat. Nos. 8,659,397; 8,668,149; U.S. Pat. Nos.
8,678,285; 8,678,286; U.S. Pat. Nos. 8,682,077; 8,687,282; U.S.
Pat. Nos. 8,692,927; 8,695,880; U.S. Pat. Nos. 8,698,949;
8,717,494; U.S. Pat. Nos. 8,717,494; 8,720,783; U.S. Pat. Nos.
8,723,804; 8,723,904; U.S. Pat. Nos. 8,727,223; D702,237; U.S. Pat.
Nos. 8,740,082; 8,740,085; U.S. Pat. Nos. 8,746,563; 8,750,445;
U.S. Pat. Nos. 8,752,766; 8,756,059; U.S. Pat. Nos. 8,757,495;
8,760,563; U.S. Pat. Nos. 8,763,909; 8,777,108; U.S. Pat. Nos.
8,777,109; 8,779,898; U.S. Pat. Nos. 8,781,520; 8,783,573; U.S.
Pat. Nos. 8,789,757; 8,789,758; U.S. Pat. Nos. 8,789,759;
8,794,520; U.S. Pat. Nos. 8,794,522; 8,794,525; U.S. Pat. Nos.
8,794,526; 8,798,367; U.S. Pat. Nos. 8,807,431; 8,807,432; U.S.
Pat. Nos. 8,820,630; 8,822,848; U.S. Pat. Nos. 8,824,692;
8,824,696; U.S. Pat. Nos. 8,842,849; 8,844,822; U.S. Pat. Nos.
8,844,823; 8,849,019; U.S. Pat. Nos. 8,851,383; 8,854,633; U.S.
Pat. Nos. 8,866,963; 8,868,421; U.S. Pat. Nos. 8,868,519;
8,868,802; U.S. Pat. Nos. 8,868,803; 8,870,074; U.S. Pat. Nos.
8,879,639; 8,880,426; U.S. Pat. Nos. 8,881,983; 8,881,987; U.S.
Pat. Nos. 8,903,172; 8,908,995; U.S. Pat. Nos. 8,910,870;
8,910,875; U.S. Pat. Nos. 8,914,290; 8,914,788; U.S. Pat. Nos.
8,915,439; 8,915,444; U.S. Pat. Nos. 8,916,789; 8,918,250; U.S.
Pat. Nos. 8,918,564; 8,925,818; U.S. Pat. Nos. 8,939,374;
8,942,480; U.S. Pat. Nos. 8,944,313; 8,944,327; U.S. Pat. Nos.
8,944,332; 8,950,678; U.S. Pat. Nos. 8,967,468; 8,971,346; U.S.
Pat. Nos. 8,976,030; 8,976,368; U.S. Pat. Nos. 8,978,981;
8,978,983; U.S. Pat. Nos. 8,978,984; 8,985,456; U.S. Pat. Nos.
8,985,457; 8,985,459; U.S. Pat. Nos. 8,985,461; 8,988,578; U.S.
Pat. Nos. 8,988,590; 8,991,704; U.S. Pat. Nos. 8,996,194;
8,996,384; U.S. Pat. Nos. 9,002,641; 9,007,368; U.S. Pat. Nos.
9,010,641; 9,015,513; U.S. Pat. Nos. 9,016,576; 9,022,288; U.S.
Pat. Nos. 9,030,964; 9,033,240; U.S. Pat. Nos. 9,033,242;
9,036,054; U.S. Pat. Nos. 9,037,344; 9,038,911; U.S. Pat. Nos.
9,038,915; 9,047,098; U.S. Pat. Nos. 9,047,359; 9,047,420; U.S.
Pat. Nos. 9,047,525; 9,047,531; U.S. Pat. Nos. 9,053,055;
9,053,378; U.S. Pat. Nos. 9,053,380; 9,058,526; U.S. Pat. Nos.
9,064,165; 9,064,167; U.S. Pat. Nos. 9,064,168; 9,064,254; U.S.
Pat. Nos. 9,066,032; 9,070,032; U.S. Design Pat. No. D716,285; U.S.
Design Pat. No. D723,560; U.S. Design Pat. No. D730,357; U.S.
Design Pat. No. D730,901; U.S. Design Pat. No. D730,902; U.S.
Design Pat. No. D733,112; U.S. Design Pat. No. D734,339;
International Publication No. 2013/163789; International
Publication No. 2013/173985; International Publication No.
2014/019130; International Publication No. 2014/110495; U.S. Patent
Application Publication No. 2008/0185432; U.S. Patent Application
Publication No. 2009/0134221; U.S. Patent Application Publication
No. 2010/0177080; U.S. Patent Application Publication No.
2010/0177076; U.S. Patent Application Publication No. 2010/0177707;
U.S. Patent Application Publication No. 2010/0177749; U.S. Patent
Application Publication No. 2010/0265880; U.S. Patent Application
Publication No. 2011/0202554; U.S. Patent Application Publication
No. 2012/0111946; U.S. Patent Application Publication No.
2012/0168511; U.S. Patent Application Publication No. 2012/0168512;
U.S. Patent Application Publication No. 2012/0193423; U.S. Patent
Application Publication No. 2012/0203647; U.S. Patent Application
Publication No. 2012/0223141; U.S. Patent Application Publication
No. 2012/0228382; U.S. Patent Application Publication No.
2012/0248188; U.S. Patent Application Publication No. 2013/0043312;
U.S. Patent Application Publication No. 2013/0082104; U.S. Patent
Application Publication No. 2013/0175341; U.S. Patent Application
Publication No. 2013/0175343; U.S. Patent Application Publication
No. 2013/0257744; U.S. Patent Application Publication No.
2013/0257759; U.S. Patent Application Publication No. 2013/0270346;
U.S. Patent Application Publication No. 2013/0287258; U.S. Patent
Application Publication No. 2013/0292475; U.S. Patent Application
Publication No. 2013/0292477; U.S. Patent Application Publication
No. 2013/0293539; U.S. Patent Application Publication No.
2013/0293540; U.S. Patent Application Publication No. 2013/0306728;
U.S. Patent Application Publication No. 2013/0306731; U.S. Patent
Application Publication No. 2013/0307964; U.S. Patent Application
Publication No. 2013/0308625; U.S. Patent Application Publication
No. 2013/0313324; U.S. Patent Application Publication No.
2013/0313325; U.S. Patent Application Publication No. 2013/0342717;
U.S. Patent Application Publication No. 2014/0001267; U.S. Patent
Application Publication No. 2014/0008439; U.S. Patent Application
Publication No. 2014/0025584; U.S. Patent Application Publication
No. 2014/0034734; U.S. Patent Application Publication No.
2014/0036848; U.S. Patent Application Publication No. 2014/0039693;
U.S. Patent Application Publication No. 2014/0042814; U.S. Patent
Application Publication No. 2014/0049120; U.S. Patent Application
Publication No. 2014/0049635; U.S. Patent Application Publication
No. 2014/0061306; U.S. Patent Application Publication No.
2014/0063289; U.S. Patent Application Publication No. 2014/0066136;
U.S. Patent Application Publication No. 2014/0067692; U.S. Patent
Application Publication No. 2014/0070005; U.S. Patent Application
Publication No. 2014/0071840; U.S. Patent Application Publication
No. 2014/0074746; U.S. Patent Application Publication No.
2014/0076974; U.S. Patent Application Publication No. 2014/0078341;
U.S. Patent Application Publication No. 2014/0078345; U.S. Patent
Application Publication No. 2014/0097249; U.S. Patent Application
Publication No. 2014/0098792; U.S. Patent Application Publication
No. 2014/0100813; U.S. Patent Application Publication No.
2014/0103115; U.S. Patent Application Publication No. 2014/0104413;
U.S. Patent Application Publication No. 2014/0104414; U.S. Patent
Application Publication No. 2014/0104416; U.S. Patent Application
Publication No. 2014/0104451; U.S. Patent Application Publication
No. 2014/0106594; U.S. Patent Application Publication No.
2014/0106725; U.S. Patent Application Publication No. 2014/0108010;
U.S. Patent Application Publication No. 2014/0108402; U.S. Patent
Application Publication No. 2014/0110485; U.S. Patent Application
Publication No. 2014/0114530; U.S. Patent Application Publication
No. 2014/0124577; U.S. Patent Application Publication No.
2014/0124579; U.S. Patent Application Publication No. 2014/0125842;
U.S. Patent Application Publication No. 2014/0125853; U.S. Patent
Application Publication No. 2014/0125999; U.S. Patent Application
Publication No. 2014/0129378; U.S. Patent Application Publication
No. 2014/0131438; U.S. Patent Application Publication No.
2014/0131441; U.S. Patent Application Publication No. 2014/0131443;
U.S. Patent Application Publication No. 2014/0131444; U.S. Patent
Application Publication No. 2014/0131445; U.S. Patent Application
Publication No. 2014/0131448; U.S. Patent Application Publication
No. 2014/0133379; U.S. Patent Application Publication No.
2014/0136208; U.S. Patent Application Publication No. 2014/0140585;
U.S. Patent Application Publication No. 2014/0151453; U.S. Patent
Application Publication No. 2014/0152882; U.S. Patent Application
Publication No. 2014/0158770; U.S. Patent Application Publication
No. 2014/0159869; U.S. Patent Application Publication No.
2014/0166755; U.S. Patent Application Publication No. 2014/0166759;
U.S. Patent Application Publication No. 2014/0168787; U.S. Patent
Application Publication No. 2014/0175165; U.S. Patent Application
Publication No. 2014/0175172; U.S. Patent Application Publication
No. 2014/0191644; U.S. Patent Application Publication No.
2014/0191913; U.S. Patent Application Publication No. 2014/0197238;
U.S. Patent Application Publication No. 2014/0197239; U.S. Patent
Application Publication No. 2014/0197304; U.S. Patent Application
Publication No. 2014/0214631; U.S. Patent Application Publication
No. 2014/0217166; U.S. Patent Application Publication No.
2014/0217180; U.S. Patent Application Publication No. 2014/0231500;
U.S. Patent Application Publication No. 2014/0232930; U.S. Patent
Application Publication No. 2014/0247315; U.S. Patent Application
Publication No. 2014/0263493; U.S. Patent Application Publication
No. 2014/0263645; U.S. Patent Application Publication No.
2014/0267609; U.S. Patent Application Publication No. 2014/0270196;
U.S. Patent Application Publication No. 2014/0270229; U.S. Patent
Application Publication No. 2014/0278387; U.S. Patent Application
Publication No. 2014/0278391; U.S. Patent Application Publication
No. 2014/0282210; U.S. Patent Application Publication No.
2014/0284384; U.S. Patent Application Publication No. 2014/0288933;
U.S. Patent Application Publication No. 2014/0297058; U.S. Patent
Application Publication No. 2014/0299665; U.S. Patent Application
Publication No. 2014/0312121; U.S. Patent Application Publication
No. 2014/0319220; U.S. Patent Application Publication No.
2014/0319221; U.S. Patent Application Publication No. 2014/0326787;
U.S. Patent Application Publication No. 2014/0332590; U.S. Patent
Application Publication No. 2014/0344943; U.S. Patent Application
Publication No. 2014/0346233; U.S. Patent Application Publication
No. 2014/0351317; U.S. Patent Application Publication No.
2014/0353373; U.S. Patent Application Publication No. 2014/0361073;
U.S. Patent Application Publication No. 2014/0361082; U.S. Patent
Application Publication No. 2014/0362184; U.S. Patent Application
Publication No. 2014/0363015; U.S. Patent Application Publication
No. 2014/0369511; U.S. Patent Application Publication No.
2014/0374483; U.S. Patent Application Publication No. 2014/0374485;
U.S. Patent Application Publication No. 2015/0001301; U.S. Patent
Application Publication No. 2015/0001304; U.S. Patent Application
Publication No. 2015/0003673; U.S. Patent Application Publication
No. 2015/0009338; U.S. Patent Application Publication No.
2015/0009610; U.S. Patent Application Publication No. 2015/0014416;
U.S. Patent Application Publication No. 2015/0021397; U.S. Patent
Application Publication No. 2015/0028102; U.S. Patent Application
Publication No. 2015/0028103; U.S. Patent Application Publication
No. 2015/0028104; U.S. Patent Application Publication No.
2015/0029002; U.S. Patent Application Publication No. 2015/0032709;
U.S. Patent Application Publication No. 2015/0039309; U.S. Patent
Application Publication No. 2015/0039878; U.S. Patent Application
Publication No. 2015/0040378; U.S. Patent Application Publication
No. 2015/0048168; U.S. Patent Application Publication No.
2015/0049347; U.S. Patent Application Publication No. 2015/0051992;
U.S. Patent Application Publication No. 2015/0053766; U.S. Patent
Application Publication No. 2015/0053768; U.S. Patent Application
Publication No. 2015/0053769; U.S. Patent Application Publication
No. 2015/0060544; U.S. Patent Application Publication No.
2015/0062366; U.S. Patent Application Publication No. 2015/0063215;
U.S. Patent Application Publication No. 2015/0063676; U.S. Patent
Application Publication No. 2015/0069130; U.S. Patent Application
Publication No. 2015/0071819; U.S. Patent Application Publication
No. 2015/0083800; U.S. Patent Application Publication No.
2015/0086114; U.S. Patent Application Publication No. 2015/0088522;
U.S. Patent Application Publication No. 2015/0096872; U.S. Patent
Application Publication No. 2015/0099557; U.S. Patent Application
Publication No. 2015/0100196; U.S. Patent Application Publication
No. 2015/0102109; U.S. Patent Application Publication No.
2015/0115035; U.S. Patent Application Publication No. 2015/0127791;
U.S. Patent Application Publication No. 2015/0128116; U.S. Patent
Application Publication No. 2015/0129659; U.S. Patent Application
Publication No. 2015/0133047; U.S. Patent Application Publication
No. 2015/0134470; U.S. Patent Application Publication No.
2015/0136851; U.S. Patent Application Publication No. 2015/0136854;
U.S. Patent Application Publication No. 2015/0142492; U.S. Patent
Application Publication No. 2015/0144692; U.S. Patent Application
Publication No. 2015/0144698; U.S. Patent Application Publication
No. 2015/0144701; U.S. Patent Application Publication No.
2015/0149946; U.S. Patent Application Publication No. 2015/0161429;
U.S. Patent Application Publication No. 2015/0169925; U.S. Patent
Application Publication No. 2015/0169929; U.S. Patent Application
Publication No. 2015/0178523; U.S. Patent Application Publication
No. 2015/0178534; U.S. Patent Application Publication No.
2015/0178535; U.S. Patent Application Publication No. 2015/0178536;
U.S. Patent Application Publication No. 2015/0178537; U.S. Patent
Application Publication No. 2015/0181093; U.S. Patent Application
Publication No. 2015/0181109; U.S. patent application Ser. No.
13/367,978 for a Laser Scanning Module Employing an Elastomeric
U-Hinge Based Laser Scanning Assembly, filed Feb. 7, 2012 (Feng et
al.); U.S. patent application Ser. No. 29/458,405 for an Electronic
Device, filed Jun. 19, 2013 (Fitch et al.); U.S. patent application
Ser. No. 29/459,620 for an Electronic Device Enclosure, filed Jul.
2, 2013 (London et al.); U.S. patent application Ser. No.
29/468,118 for an Electronic Device Case, filed Sep. 26, 2013
(Oberpriller et al.); U.S. patent application Ser. No. 14/150,393
for Indicia-reader Having Unitary Construction Scanner, filed Jan.
8, 2014 (Colavito et al.); U.S. patent application Ser. No.
14/200,405 for Indicia Reader for Size-Limited Applications filed
Mar. 7, 2014 (Feng et al.); U.S. patent application Ser. No.
14/231,898 for Hand-Mounted Indicia-Reading Device with Finger
Motion Triggering filed Apr. 1, 2014 (Van Horn et al.); U.S. patent
application Ser. No. 29/486,759 for an Imaging Terminal, filed Apr.
2, 2014 (Oberpriller et al.); U.S. patent application Ser. No.
14/257,364 for Docking System and Method Using Near Field
Communication filed Apr. 21, 2014 (Showering); U.S. patent
application Ser. No. 14/264,173 for Autofocus Lens System for
Indicia Readers filed Apr. 29, 2014 (Ackley et al.); U.S. patent
application Ser. No. 14/277,337 for MULTIPURPOSE OPTICAL READER,
filed May 14, 2014 (Jovanovski et al.); U.S. patent application
Ser. No. 14/283,282 for TERMINAL HAVING ILLUMINATION AND FOCUS
CONTROL filed May 21, 2014 (Liu et al.); U.S. patent application
Ser. No. 14/327,827 for a MOBILE-PHONE ADAPTER FOR ELECTRONIC
TRANSACTIONS, filed Jul. 10, 2014 (Hejl); U.S. patent application
Ser. No. 14/334,934 for a SYSTEM AND METHOD FOR INDICIA
VERIFICATION, filed Jul. 18, 2014 (Hejl); U.S. patent application
Ser. No. 14/339,708 for LASER SCANNING CODE SYMBOL READING SYSTEM,
filed Jul. 24, 2014 (Xian et al.); U.S. patent application Ser. No.
14/340,627 for an AXIALLY REINFORCED FLEXIBLE SCAN ELEMENT, filed
Jul. 25, 2014 (Rueblinger et al.); U.S. patent application Ser. No.
14/446,391 for MULTIFUNCTION POINT OF SALE APPARATUS WITH OPTICAL
SIGNATURE CAPTURE filed Jul. 30, 2014 (Good et al.); U.S. patent
application Ser. No. 14/452,697 for INTERACTIVE INDICIA READER,
filed Aug. 6, 2014 (Todeschini); U.S. patent application Ser. No.
14/453,019 for DIMENSIONING SYSTEM WITH GUIDED ALIGNMENT, filed
Aug. 6, 2014 (Li et al.); U.S. patent application Ser. No.
14/462,801 for MOBILE COMPUTING DEVICE WITH DATA COGNITION
SOFTWARE, filed on Aug. 19, 2014 (Todeschini et al.); U.S. patent
application Ser. No. 14/483,056 for VARIABLE DEPTH OF FIELD BARCODE
SCANNER filed Sep. 10, 2014 (McCloskey et al.); U.S. patent
application Ser. No. 14/513,808 for IDENTIFYING INVENTORY ITEMS IN
A STORAGE FACILITY filed Oct. 14, 2014 (Singel et al.); U.S. patent
application Ser. No. 14/519,195 for HANDHELD DIMENSIONING SYSTEM
WITH FEEDBACK filed Oct. 21, 2014 (Laffargue et al.); U.S. patent
application Ser. No. 14/519,179 for DIMENSIONING SYSTEM WITH
MULTIPATH INTERFERENCE MITIGATION filed Oct. 21, 2014 (Thuries et
al.); U.S. patent application Ser. No. 14/519,211 for SYSTEM AND
METHOD FOR DIMENSIONING filed Oct. 21, 2014 (Ackley et al.); U.S.
patent application Ser. No. 14/519,233 for HANDHELD DIMENSIONER
WITH DATA-QUALITY INDICATION filed Oct. 21, 2014 (Laffargue et
al.); U.S. patent application Ser. No. 14/519,249 for HANDHELD
DIMENSIONING SYSTEM WITH MEASUREMENT-CONFORMANCE FEEDBACK filed
Oct. 21, 2014 (Ackley et al.); U.S. patent application Ser. No.
14/527,191 for METHOD AND SYSTEM FOR RECOGNIZING SPEECH USING
WILDCARDS IN AN EXPECTED RESPONSE filed Oct. 29, 2014 (Braho et
al.); U.S. patent application Ser. No. 14/529,563 for ADAPTABLE
INTERFACE FOR A MOBILE COMPUTING DEVICE filed Oct. 31, 2014 (Schoon
et al.); U.S. patent application Ser. No. 14/529,857 for BARCODE
READER WITH SECURITY FEATURES filed Oct. 31, 2014 (Todeschini et
al.); U.S. patent application Ser. No. 14/398,542 for PORTABLE
ELECTRONIC DEVICES HAVING A SEPARATE LOCATION TRIGGER UNIT FOR USE
IN CONTROLLING AN APPLICATION UNIT filed Nov. 3, 2014 (Bian et
al.); U.S. patent application Ser. No. 14/531,154 for DIRECTING AN
INSPECTOR THROUGH AN INSPECTION filed Nov. 3, 2014 (Miller et al.);
U.S. patent application Ser. No. 14/533,319 for BARCODE SCANNING
SYSTEM USING WEARABLE DEVICE WITH EMBEDDED CAMERA filed Nov. 5,
2014 (Todeschini); U.S. patent application Ser. No. 14/535,764 for
CONCATENATED EXPECTED RESPONSES FOR SPEECH RECOGNITION filed Nov.
7, 2014 (Braho et al.); U.S. patent application Ser. No. 14/568,305
for AUTO-CONTRAST VIEWFINDER FOR AN INDICIA READER filed Dec. 12,
2014 (Todeschini); U.S. patent application Ser. No. 14/573,022 for
DYNAMIC DIAGNOSTIC INDICATOR GENERATION filed Dec. 17, 2014
(Goldsmith); U.S. patent application Ser. No. 14/578,627 for SAFETY
SYSTEM AND METHOD filed Dec. 22, 2014 (Ackley et al.); U.S. patent
application Ser. No. 14/580,262 for MEDIA GATE FOR THERMAL TRANSFER
PRINTERS filed Dec. 23, 2014 (Bowles); U.S. patent application Ser.
No. 14/590,024 for SHELVING AND PACKAGE LOCATING SYSTEMS FOR
DELIVERY VEHICLES filed Jan. 6, 2015 (Payne); U.S. patent
application Ser. No. 14/596,757 for SYSTEM AND METHOD FOR DETECTING
BARCODE PRINTING ERRORS filed Jan. 14, 2015 (Ackley); U.S. patent
application Ser. No. 14/416,147 for OPTICAL READING APPARATUS
HAVING VARIABLE SETTINGS filed Jan. 21, 2015 (Chen et al.); U.S.
patent application Ser. No. 14/614,706 for DEVICE FOR SUPPORTING AN
ELECTRONIC TOOL ON A USER'S HAND filed Feb. 5, 2015 (Oberpriller et
al.); U.S. patent application Ser. No. 14/614,796 for CARGO
APPORTIONMENT TECHNIQUES filed Feb. 5, 2015 (Morton et al.); U.S.
patent application Ser. No. 29/516,892 for TABLE COMPUTER filed
Feb. 6, 2015 (Bidwell et al.); U.S. patent application Ser. No.
14/619,093 for METHODS FOR TRAINING A SPEECH RECOGNITION SYSTEM
filed Feb. 11, 2015 (Pecorari); U.S. patent application Ser. No.
14/628,708 for DEVICE, SYSTEM, AND METHOD FOR DETERMINING THE
STATUS OF CHECKOUT LANES filed Feb. 23, 2015 (Todeschini); U.S.
patent application Ser. No. 14/630,841 for TERMINAL INCLUDING
IMAGING ASSEMBLY filed Feb. 25, 2015 (Gomez et al.); U.S. patent
application Ser. No. 14/635,346 for SYSTEM AND METHOD FOR RELIABLE
STORE-AND-FORWARD DATA HANDLING BY ENCODED INFORMATION READING
TERMINALS filed Mar. 2, 2015 (Sevier); U.S. patent application Ser.
No. 29/519,017 for SCANNER filed Mar. 2, 2015 (Zhou et al.); U.S.
patent application Ser. No. 14/405,278 for DESIGN PATTERN FOR
SECURE STORE filed Mar. 9, 2015 (Zhu et al.); U.S. patent
application Ser. No. 14/660,970 for DECODABLE INDICIA READING
TERMINAL WITH COMBINED ILLUMINATION filed Mar. 18, 2015 (Kearney et
al.); U.S. patent application Ser. No. 14/661,013 for REPROGRAMMING
SYSTEM AND METHOD FOR DEVICES INCLUDING PROGRAMMING SYMBOL filed
Mar. 18, 2015 (Soule et al.); U.S. patent application Ser. No.
14/662,922 for MULTIFUNCTION POINT OF SALE SYSTEM filed Mar. 19,
2015 (Van Horn et al.); U.S. patent application Ser. No. 14/663,638
for VEHICLE MOUNT COMPUTER WITH CONFIGURABLE IGNITION SWITCH
BEHAVIOR filed Mar. 20, 2015 (Davis et al.); U.S. patent
application Ser. No. 14/664,063 for METHOD AND APPLICATION FOR
SCANNING A BARCODE WITH A SMART DEVICE WHILE CONTINUOUSLY RUNNING
AND DISPLAYING AN APPLICATION ON THE SMART DEVICE DISPLAY filed
Mar. 20, 2015 (Todeschini); U.S. patent application Ser. No.
14/669,280 for TRANSFORMING COMPONENTS OF A WEB PAGE TO VOICE
PROMPTS filed Mar. 26, 2015 (Funyak et al.); U.S. patent
application Ser. No. 14/674,329 for AIMER FOR BARCODE SCANNING
filed Mar. 31, 2015 (Bidwell); U.S. patent application Ser. No.
14/676,109 for INDICIA READER filed Apr. 1, 2015 (Huck); U.S.
patent application Ser. No. 14/676,327 for DEVICE MANAGEMENT PROXY
FOR SECURE DEVICES filed Apr. 1, 2015 (Yeakley et al.); U.S. patent
application Ser. No. 14/676,898 for NAVIGATION SYSTEM CONFIGURED TO
INTEGRATE MOTION SENSING DEVICE INPUTS filed Apr. 2, 2015
(Showering); U.S. patent application Ser. No. 14/679,275 for
DIMENSIONING SYSTEM CALIBRATION SYSTEMS AND METHODS filed Apr. 6,
2015 (Laffargue et al.); U.S. patent application Ser. No.
29/523,098 for HANDLE FOR A TABLET COMPUTER filed Apr. 7, 2015
(Bidwell et al.); U.S. patent application Ser. No. 14/682,615 for
SYSTEM AND METHOD FOR POWER MANAGEMENT OF MOBILE DEVICES filed Apr.
9, 2015 (Murawski et al.); U.S. patent application Ser. No.
14/686,822 for MULTIPLE PLATFORM SUPPORT SYSTEM AND METHOD filed
Apr. 15, 2015 (Qu et al.); U.S. patent application Ser. No.
14/687,289 for SYSTEM FOR COMMUNICATION VIA A PERIPHERAL HUB filed
Apr. 15, 2015 (Kohtz et al.); U.S. patent application Ser. No.
29/524,186 for SCANNER filed Apr. 17, 2015 (Zhou et al.); U.S.
patent application Ser. No. 14/695,364 for MEDICATION MANAGEMENT
SYSTEM filed Apr. 24, 2015 (Sewell et al.); U.S. patent application
Ser. No. 14/695,923 for SECURE UNATTENDED NETWORK AUTHENTICATION
filed Apr. 24, 2015 (Kubler et al.); U.S. patent application Ser.
No. 29/525,068 for TABLET COMPUTER WITH REMOVABLE SCANNING DEVICE
filed Apr. 27, 2015 (Schulte et al.); U.S. patent application Ser.
No. 14/699,436 for SYMBOL READING SYSTEM HAVING PREDICTIVE
DIAGNOSTICS filed Apr. 29, 2015 (Nahill et al.); U.S. patent
application Ser. No. 14/702,110 for SYSTEM AND METHOD FOR
REGULATING BARCODE DATA INJECTION INTO A RUNNING APPLICATION ON A
SMART DEVICE filed May 1, 2015 (Todeschini et al.); U.S. patent
application Ser. No. 14/702,979 for TRACKING BATTERY CONDITIONS
filed May 4, 2015 (Young et al.); U.S. patent application Ser. No.
14/704,050 for INTERMEDIATE LINEAR POSITIONING filed May 5, 2015
(Charpentier et al.); U.S. patent application Ser. No. 14/705,012
for HANDS-FREE HUMAN MACHINE INTERFACE RESPONSIVE TO A DRIVER OF A
VEHICLE filed May 6, 2015 (Fitch et al.); U.S. patent application
Ser. No. 14/705,407 for METHOD AND SYSTEM TO PROTECT SOFTWARE-BASED
NETWORK-CONNECTED DEVICES FROM ADVANCED PERSISTENT THREAT filed May
6, 2015 (Hussey et al.); U.S. patent application Ser. No.
14/707,037 for SYSTEM AND METHOD FOR DISPLAY OF INFORMATION USING A
VEHICLE-MOUNT COMPUTER filed May 8, 2015 (Chamberlin); U.S. patent
application Ser. No. 14/707,123 for APPLICATION INDEPENDENT DEX/UCS
INTERFACE filed May 8, 2015 (Pape); U.S. patent application Ser.
No. 14/707,492 for METHOD AND APPARATUS FOR READING OPTICAL INDICIA
USING A PLURALITY OF DATA SOURCES filed May 8, 2015 (Smith et al.);
U.S. patent application Ser. No. 14/710,666 for PRE-PAID USAGE
SYSTEM FOR ENCODED INFORMATION READING TERMINALS filed May 13, 2015
(Smith); U.S. patent application Ser. No. 29/526,918 for CHARGING
BASE filed May 14, 2015 (Fitch et al.); U.S. patent application
Ser. No. 14/715,672 for AUGUMENTED REALITY ENABLED HAZARD DISPLAY
filed May 19, 2015 (Venkatesha et al.); U.S. patent application
Ser. No. 14/715,916 for EVALUATING IMAGE VALUES filed May 19, 2015
(Ackley); U.S. patent application Ser. No. 14/722,608 for
INTERACTIVE USER INTERFACE FOR CAPTURING A DOCUMENT IN AN IMAGE
SIGNAL filed May 27, 2015 (Showering et al.); U.S. patent
application Ser. No. 29/528,165 for IN-COUNTER BARCODE SCANNER
filed May 27, 2015 (Oberpriller et al.); U.S. patent application
Ser. No. 14/724,134 for ELECTRONIC DEVICE WITH WIRELESS PATH
SELECTION CAPABILITY filed May 28, 2015 (Wang et al.); U.S. patent
application Ser. No. 14/724,849 for METHOD OF PROGRAMMING THE
DEFAULT CABLE INTERFACE SOFTWARE IN AN INDICIA READING DEVICE filed
May 29, 2015 (Barten); U.S. patent application Ser. No. 14/724,908
for IMAGING APPARATUS HAVING IMAGING ASSEMBLY filed May 29, 2015
(Barber et al.); U.S. patent application Ser. No. 14/725,352 for
APPARATUS AND METHODS FOR MONITORING ONE OR MORE PORTABLE DATA
TERMINALS (Caballero et al.); U.S. patent application Ser. No.
29/528,590 for ELECTRONIC DEVICE filed May 29, 2015 (Fitch et al.);
U.S. patent application Ser. No. 29/528,890 for MOBILE COMPUTER
HOUSING filed Jun. 2, 2015 (Fitch et al.); U.S. patent application
Ser. No. 14/728,397 for DEVICE MANAGEMENT USING VIRTUAL INTERFACES
CROSS-REFERENCE TO RELATED APPLICATIONS filed Jun. 2, 2015
(Caballero); U.S. patent application Ser. No. 14/732,870 for DATA
COLLECTION MODULE AND SYSTEM filed Jun. 8, 2015 (Powilleit); U.S.
patent application Ser. No. 29/529,441 for INDICIA READING DEVICE
filed Jun. 8, 2015 (Zhou et al.); U.S. patent application Ser. No.
14/735,717 for INDICIA-READING SYSTEMS HAVING AN INTERFACE WITH A
USER'S NERVOUS SYSTEM filed Jun. 10, 2015 (Todeschini); U.S. patent
application Ser. No. 14/738,038 for METHOD OF AND SYSTEM FOR
DETECTING OBJECT WEIGHING INTERFERENCES filed Jun. 12, 2015
(Amundsen et al.); U.S. patent application Ser. No. 14/740,320 for
TACTILE SWITCH FOR A MOBILE ELECTRONIC DEVICE filed Jun. 16, 2015
(Bandringa); U.S. patent application Ser. No. 14/740,373 for
CALIBRATING A VOLUME DIMENSIONER filed Jun. 16, 2015 (Ackley et
al.); U.S. patent application Ser. No. 14/742,818 for INDICIA
READING SYSTEM EMPLOYING DIGITAL GAIN CONTROL filed Jun. 18, 2015
(Xian et al.); U.S. patent application Ser. No. 14/743,257 for
WIRELESS MESH POINT PORTABLE DATA TERMINAL filed Jun. 18, 2015
(Wang et al.); U.S. patent application Ser. No. 29/530,600 for
CYCLONE filed Jun. 18, 2015 (Vargo et al); U.S. patent application
Ser. No. 14/744,633 for IMAGING APPARATUS COMPRISING IMAGE SENSOR
ARRAY HAVING SHARED GLOBAL SHUTTER CIRCUITRY filed Jun. 19, 2015
(Wang); U.S. patent application Ser. No. 14/744,836 for CLOUD-BASED
SYSTEM FOR READING OF DECODABLE INDICIA filed Jun. 19, 2015
(Todeschini et al.); U.S. patent application Ser. No. 14/745,006
for SELECTIVE OUTPUT OF DECODED MESSAGE DATA filed Jun. 19, 2015
(Todeschini et al.); U.S. patent application Ser. No. 14/747,197
for OPTICAL PATTERN PROJECTOR filed Jun. 23, 2015 (Thuries et al.);
U.S. patent application Ser. No. 14/747,490 for DUAL-PROJECTOR
THREE-DIMENSIONAL SCANNER filed Jun. 23, 2015 (Jovanovski et al.);
and U.S. patent application Ser. No. 14/748,446 for CORDLESS
INDICIA READER WITH A MULTIFUNCTION COIL FOR WIRELESS CHARGING AND
EAS DEACTIVATION, filed Jun. 24, 2015 (Xie et al.).
In the specification and/or figures, typical embodiments of the
invention have been disclosed. The present invention is not limited
to such exemplary embodiments. The use of the term "and/or"
includes any and all combinations of one or more of the associated
listed items. The figures are schematic representations and so are
not necessarily drawn to scale. Unless otherwise noted, specific
terms have been used in a generic and descriptive sense and not for
purposes of limitation.
The foregoing detailed description has set forth various
embodiments of the devices and/or processes via the use of block
diagrams, flow charts, schematics, exemplary data structures, and
examples. Insofar as such block diagrams, flow charts, schematics,
exemplary data structures, and examples contain one or more
functions and/or operations, it will be understood by those skilled
in the art that each function and/or operation within such block
diagrams, flowcharts, schematics, exemplary data structures, or
examples can be implemented, individually and/or collectively, by a
wide range of hardware, software, firmware, or virtually any
combination thereof.
In one embodiment, the present subject matter may be implemented
via Application Specific Integrated Circuits (ASICs). However,
those skilled in the art will recognize that the embodiments
disclosed herein, in whole or in part, can be equivalently
implemented in standard integrated circuits, as one or more
computer programs running on one or more computers (e.g., as one or
more programs running on one or more computer systems), as one or
more programs running on one or more controllers (e.g.,
microcontrollers) as one or more programs running on one or more
processors (e.g., microprocessors), as firmware, or as virtually
any combination thereof, and that designing the circuitry and/or
writing the code for the software and or firmware would be well
within the skill of one of ordinary skill in the art in light of
this disclosure.
In addition, those skilled in the art will appreciate that the
control mechanisms taught herein are capable of being distributed
as a program product in a variety of tangible forms, and that an
illustrative embodiment applies equally regardless of the
particular type of tangible instruction bearing media used to
actually carry out the distribution. Examples of tangible
instruction bearing media include, but are not limited to, the
following: recordable type media such as floppy disks, hard disk
drives, CD ROMs, digital tape, flash drives, and computer
memory.
The various embodiments described above can be combined to provide
further embodiments. These and other changes can be made to the
present systems and methods in light of the above-detailed
description. In general, in the following claims, the terms used
should not be construed to limit the invention to the specific
embodiments disclosed in the specification and the claims, but
should be construed to include all machine-readable symbol scanning
and processing systems and methods that read in accordance with the
claims. Accordingly, the invention is not limited by the
disclosure, but instead its scope is to be determined entirely by
the following claims.
* * * * *